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	Commit message (Collapse)	Author	Age
*	LoopVectorizer: Keep track of conditional store basic blocks	Arnold Schwaighofer	2014-02-08
\| \| \| \| \| \| \| \| \| \| \| \| \|	Before conditional store vectorization/unrolling we had only one vectorized/unrolled basic block. After adding support for conditional store vectorization this will not only be one block but multiple basic blocks. The last block would have the back-edge. I updated the code to use a vector of basic blocks instead of a single basic block and fixed the users to use the last entry in this vector. But, I forgot to add the basic blocks to this vector! Fixes PR18724. git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@201028 91177308-0d34-0410-b5e6-96231b3b80d8
*	LoopVectorize: Support conditional stores by scalarizing	Arnold Schwaighofer	2014-01-28
	The vectorizer takes a loop like this and widens all instructions except for the store. The stores are scalarized/unrolled and hidden behind an "if" block. for (i = 0; i < 128; ++i) { if (a[i] < 10) a[i] += val; } for (i = 0; i < 128; i+=2) { v = a[i:i+1]; v0 = (extract v, 0) + 10; v1 = (extract v, 1) + 10; if (v0 < 10) a[i] = v0; if (v1 < 10) a[i] = v1; } The vectorizer relies on subsequent optimizations to sink instructions into the conditional block where they are anticipated. The flag "vectorize-num-stores-pred" controls whether and how many stores to handle this way. Vectorization of conditional stores is disabled per default for now. This patch also adds a change to the heuristic when the flag "enable-loadstore-runtime-unroll" is enabled (off by default). It unrolls small loops until load/store ports are saturated. This heuristic uses TTI's getMaxUnrollFactor as a measure for load/store ports. I also added a second flag -enable-cond-stores-vec. It will enable vectorization of conditional stores. But there is no cost model for vectorization of conditional stores in place yet so this will not do good at the moment. rdar://15892953 Results for x86-64 -O3 -mavx +/- -mllvm -enable-loadstore-runtime-unroll -vectorize-num-stores-pred=1 (before the BFI change): Performance Regressions: Benchmarks/Ptrdist/yacr2/yacr2 7.35% (maze3() is identical but 10% slower) Applications/siod/siod 2.18% Performance improvements: mesa -4.42% libquantum -4.15% With a patch that slightly changes the register heuristics (by subtracting the induction variable on both sides of the register pressure equation, as the induction variable is probably not really unrolled): Performance Regressions: Benchmarks/Ptrdist/yacr2/yacr2 7.73% Applications/siod/siod 1.97% Performance Improvements: libquantum -13.05% (we now also unroll quantum_toffoli) mesa -4.27% git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@200270 91177308-0d34-0410-b5e6-96231b3b80d8